Applied Scientist II, SSG Science

About the Role

Amazon Devices is a pioneering R&D division responsible for iconic products such as the Kindle range, Fire Tablets, Fire TV, Health Wellness devices, Amazon Echo, and Astro. This role offers a unique chance to contribute to the advancement of cutting-edge techniques that enable Generative AI deployment on edge devices. We seek distinguished scientists to join our Applied Science team to innovate and optimize the next wave of edge models through close integration with custom machine learning hardware built on breakthrough architectures. Embrace challenges, enjoy the process, and create impactful innovations.

Key Responsibilities

• Optimize Gen AI models for edge platforms through quantization, pruning, distillation, and fine-tuning techniques.
• Develop deep insights into Amazon’s proprietary Neural Edge Engine, inventing novel optimization methods.
• Examine deep learning workloads and offer expert advice on mapping them efficiently to the Neural Edge Engine.
• Leverage foundational principles from Information Theory, Scientific Computing, Deep Learning Theory, and Non-Equilibrium Thermodynamics to guide work.
• Train custom Gen AI models that exceed current state-of-the-art standards and pave the way for scalable production solutions.
• Work collaboratively with compiler engineers, fellow scientists, hardware architects, and product teams to deliver ML-focused solutions for devices.
• Contribute to the scientific community by publishing open source work and representing Amazon at leading conferences such as NeurIPS, ICLR, and MLSys.

Required Qualifications

• At least 2 years of experience constructing machine learning models for practical business applications.
• PhD or Master’s degree with over 4 years' experience in computer science, computer engineering, machine learning, or related domains.
• Track record of inventions or scientific publications in top-tier peer-reviewed venues.
• Proficient programming skills in Java, C++, Python, or comparable languages.
• Expertise in one or more areas including algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, or high-performance computing.
• Solid understanding of mathematical foundations such as linear algebra and calculus.

Preferred Qualifications

• Experience in professional software engineering environments.
• Prior involvement in deploying ML models in production and overseeing their complete lifecycle from development through deployment.

Additional Information

Amazon fosters an inclusive culture that empowers employees to achieve optimal results. Candidates requiring accommodations due to disabilities during hiring or onboarding processes can seek assistance. For further details, please reach out to the local recruiting team.